The use of up-to-date artificial intelligence systems to estimate and predict accurately the rechargeable battery life of modern electric cars is becoming a fairly common approach. After all, the incorrect and inadequate assessment of the electric car's operation affects the timeliness of its maintenance, which in turn impacts the overall service life of the most important mechanisms and parts of the car, in particular the engine and the battery. This article discusses the concept of using a cyber-physical system to predict the Road Range and the State of Health of an electric car based on the use of soft computing ap-proaches (ANFIS). This made it possible to determine more accurately the individual Road Range and the State of Health indicators of an electric car depending on many parameters (temperature, driver's driving style and the current BMS indicators of the battery). The proposed approach can be used in IoT networks in order to obtain more accurate information from data of more cars.